Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_plm_modulof1_20261104-181434

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
train2.67030.47360.50300.18374756.00000.047816499.00000.4000-0.68871.15250.00000.00000.10080.5400-0.01003.81510.00000.00000.23020.5200-0.02833.81510.01000.00000.24860.5000-0.20623.87920.02990.00000.2466
validation4.34750.31880.33430.0960819.0000-0.08192861.00000.3000-0.48221.19360.00000.00000.09060.3000-0.61042.25020.00000.00000.08480.3500-0.66223.15840.00000.00000.08460.3750-0.41262.25020.00000.00000.1115
test2.72150.34790.37080.1064571.00000.03301359.00000.4000-0.21510.44100.00000.00000.24020.3600-0.40671.57620.00000.00000.26520.3900-0.25741.87170.06000.00000.34660.4194-0.15021.57620.00000.00000.2971

Loss per epoch

training validation

Config

name: reference_ube4b_fc_plm_modulof1
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 1
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7